Edit model card
TensorBlock

Feedback and support: TensorBlock's Twitter/X, Telegram Group and Discord server

jondurbin/bagel-dpo-34b-v0.2 - GGUF

This repo contains GGUF format model files for jondurbin/bagel-dpo-34b-v0.2.

The files were quantized using machines provided by TensorBlock, and they are compatible with llama.cpp as of commit b4011.

Prompt template

[INST] <<SYS>>
{system_prompt}
<</SYS>>

{prompt} [/INST]

Model file specification

Filename Quant type File Size Description
bagel-dpo-34b-v0.2-Q2_K.gguf Q2_K 11.944 GB smallest, significant quality loss - not recommended for most purposes
bagel-dpo-34b-v0.2-Q3_K_S.gguf Q3_K_S 13.933 GB very small, high quality loss
bagel-dpo-34b-v0.2-Q3_K_M.gguf Q3_K_M 15.511 GB very small, high quality loss
bagel-dpo-34b-v0.2-Q3_K_L.gguf Q3_K_L 16.894 GB small, substantial quality loss
bagel-dpo-34b-v0.2-Q4_0.gguf Q4_0 18.130 GB legacy; small, very high quality loss - prefer using Q3_K_M
bagel-dpo-34b-v0.2-Q4_K_S.gguf Q4_K_S 18.253 GB small, greater quality loss
bagel-dpo-34b-v0.2-Q4_K_M.gguf Q4_K_M 19.240 GB medium, balanced quality - recommended
bagel-dpo-34b-v0.2-Q5_0.gguf Q5_0 22.080 GB legacy; medium, balanced quality - prefer using Q4_K_M
bagel-dpo-34b-v0.2-Q5_K_S.gguf Q5_K_S 22.080 GB large, low quality loss - recommended
bagel-dpo-34b-v0.2-Q5_K_M.gguf Q5_K_M 22.651 GB large, very low quality loss - recommended
bagel-dpo-34b-v0.2-Q6_K.gguf Q6_K 26.276 GB very large, extremely low quality loss
bagel-dpo-34b-v0.2-Q8_0.gguf Q8_0 34.033 GB very large, extremely low quality loss - not recommended

Downloading instruction

Command line

Firstly, install Huggingface Client

pip install -U "huggingface_hub[cli]"

Then, downoad the individual model file the a local directory

huggingface-cli download tensorblock/bagel-dpo-34b-v0.2-GGUF --include "bagel-dpo-34b-v0.2-Q2_K.gguf" --local-dir MY_LOCAL_DIR

If you wanna download multiple model files with a pattern (e.g., *Q4_K*gguf), you can try:

huggingface-cli download tensorblock/bagel-dpo-34b-v0.2-GGUF --local-dir MY_LOCAL_DIR --local-dir-use-symlinks False --include='*Q4_K*gguf'
Downloads last month
203
GGUF
Model size
34.4B params
Architecture
llama

2-bit

3-bit

4-bit

5-bit

6-bit

8-bit

Inference API
Unable to determine this model's library. Check the docs .

Model tree for tensorblock/bagel-dpo-34b-v0.2-GGUF

Quantized
(6)
this model

Datasets used to train tensorblock/bagel-dpo-34b-v0.2-GGUF